# initialize --------------------------------------------------------------

library(BlockChainPublic)
library(magrittr)
library(foreach)
## Warning: package 'foreach' was built under R version 4.0.5
library(modelsummary)
## Warning: package 'modelsummary' was built under R version 4.0.5
library(ggplot2)
## Warning: package 'ggplot2' was built under R version 4.0.5
library(rdmulti)
## Warning: package 'rdmulti' was built under R version 4.0.5
library(knitr)
library(kableExtra)
## Warning: package 'kableExtra' was built under R version 4.0.5
# read data ---------------------------------------------------------------

currency_week_hashrate <- readRDS(file = here::here("cleaned/currency_week_hashrate.rds"))
currency_algo_date <- readRDS(file = here::here("output/currency_algo_date.rds"))
asic_spec_top <- readRDS(file = here::here("output/asic_spec_top.rds"))
epoch_currency <- readRDS(file = here::here("output/epoch_currency_sha256.rds"))
# set color
colour_palette <- 
  list(
    "btc" = "#F7931A",
    "bch" = "#0AC18E",
    "bsv" = "#00368C"
  )

# Set cutoff date
cutoff_date <- epoch_currency %>% 
  dplyr::group_by(currency) %>% 
  dplyr::filter(blockheight == 630000) %>% 
  dplyr::summarize(cutoff_date = datetime[epoch == min(epoch)])

kable(cutoff_date)
currency cutoff_date
BCH 2020-04-08 12:19:24
BSV 2020-04-10 00:48:30
BTC 2020-05-11 19:23:43

RDD around the reward change

Reward change around BTC halving (esmv)

Effects on BTC

target <- "BTC"
base <- "BTC"
cutoff <- 630000
h <- 3600 * 24 * 28
h_short <- 3600 * 24 * 2
original <- TRUE
binselect <- "esmv"
p <- 4
halving_line_s <- as.POSIXct(
  c("2020-05-11 19:23:43"),
  origin = "1970-01-01",
  tz = "UTC"
  ) %>% 
  as.numeric()
halving_line_l <- as.POSIXct(
  c("2020-05-11 19:23:43"),
  origin = "1970-01-01",
  tz = "UTC"
  ) %>% 
  as.numeric()
linetype_l <- "blank"
linetype_s <- "solid"
target_before <- "BSV"
target_after <- "BCH" 


output <- 
  perform_rdd_reward_change(
    epoch_currency,
    target,
    base,
    cutoff,
    h,
    h_short,
    original,
    binselect,
    p,
    halving_line_l,
    halving_line_s,
    linetype_l,
    linetype_s,
    palette = colour_palette$btc,
    target_before,
    target_after,
    target_line = FALSE
  )
Block time (s): Optimal h
term estimate std.error statistic p.value conf.low conf.high nobs.left nobs.right nobs.effective.left nobs.effective.right h.left h.right b.left b.right cutoff order.regression order.bias kernel bwselect
Conventional 96.54 53.22 1.81 0.07 -7.78 200.85 4188.00 3755.00 1269.00 952.00 719854.32 674186.61 1148451.04 1132710.90 1589225023.00 2.00 2.00 Triangular msetwo
Bias-Corrected 86.85 53.22 1.63 0.10 -17.46 191.17 4188.00 3755.00 1269.00 952.00 719854.32 674186.61 1148451.04 1132710.90 1589225023.00 2.00 2.00 Triangular msetwo
Robust 86.85 61.67 1.41 0.16 -34.02 207.73 4188.00 3755.00 1269.00 952.00 719854.32 674186.61 1148451.04 1132710.90 1589225023.00 2.00 2.00 Triangular msetwo
Log of hash rate (h/s): Optimal h
term estimate std.error statistic p.value conf.low conf.high nobs.left nobs.right nobs.effective.left nobs.effective.right h.left h.right b.left b.right cutoff order.regression order.bias kernel bwselect
Conventional -0.13 0.11 -1.12 0.26 -0.34 0.09 4188.00 3755.00 1032.00 1302.00 586769.17 928234.16 944871.85 1452467.28 1589225023.00 2.00 2.00 Triangular msetwo
Bias-Corrected -0.12 0.11 -1.07 0.28 -0.34 0.10 4188.00 3755.00 1032.00 1302.00 586769.17 928234.16 944871.85 1452467.28 1589225023.00 2.00 2.00 Triangular msetwo
Robust -0.12 0.13 -0.90 0.37 -0.38 0.14 4188.00 3755.00 1032.00 1302.00 586769.17 928234.16 944871.85 1452467.28 1589225023.00 2.00 2.00 Triangular msetwo 
output_btc_on_btc <- output

Effects on BCH

target <- "BCH"
base <- "BTC"
cutoff <- 630000
h <- 3600 * 24 * 28
h_short <- 3600 * 24 * 2 
original <- TRUE
binselect <- "esmv"
p <- 4
halving_line_s <- as.POSIXct(
  c("2020-05-11 19:23:43"),
  origin = "1970-01-01",
  tz = "UTC"
  ) %>% 
  as.numeric()
halving_line_l <- as.POSIXct(
  c("2020-05-11 19:23:43"),
  origin = "1970-01-01",
  tz = "UTC"
  ) %>% 
  as.numeric()
linetype_l <- "blank"
linetype_s <- "solid"
target_before <- "BSV"
target_after <- "BCH" 

output <- 
  perform_rdd_reward_change(
    epoch_currency,
    target,
    base,
    cutoff,
    h,
    h_short,
    original,
    binselect,
    p,
    halving_line_l,
    halving_line_s,
    linetype_l,
    linetype_s,
    palette = colour_palette$bch,
    target_before,
    target_after,
    target_line = FALSE
  )
Block time (s): Optimal h
term estimate std.error statistic p.value conf.low conf.high nobs.left nobs.right nobs.effective.left nobs.effective.right h.left h.right b.left b.right cutoff order.regression order.bias kernel bwselect
Conventional 18.06 56.70 0.32 0.75 -93.06 129.18 4011.00 4020.00 1107.00 1063.00 664799.29 640430.51 1082126.18 999375.58 1589225023.00 2.00 2.00 Triangular msetwo
Bias-Corrected 17.54 56.70 0.31 0.76 -93.59 128.66 4011.00 4020.00 1107.00 1063.00 664799.29 640430.51 1082126.18 999375.58 1589225023.00 2.00 2.00 Triangular msetwo
Robust 17.54 65.09 0.27 0.79 -110.03 145.11 4011.00 4020.00 1107.00 1063.00 664799.29 640430.51 1082126.18 999375.58 1589225023.00 2.00 2.00 Triangular msetwo
Log of hash rate (h/s): Optimal h
term estimate std.error statistic p.value conf.low conf.high nobs.left nobs.right nobs.effective.left nobs.effective.right h.left h.right b.left b.right cutoff order.regression order.bias kernel bwselect
Conventional 0.38 0.11 3.30 0.00 0.15 0.60 4011.00 4020.00 1215.00 1237.00 717525.59 755638.86 1257452.96 1245568.57 1589225023.00 2.00 2.00 Triangular msetwo
Bias-Corrected 0.38 0.11 3.29 0.00 0.15 0.60 4011.00 4020.00 1215.00 1237.00 717525.59 755638.86 1257452.96 1245568.57 1589225023.00 2.00 2.00 Triangular msetwo
Robust 0.38 0.13 2.89 0.00 0.12 0.63 4011.00 4020.00 1215.00 1237.00 717525.59 755638.86 1257452.96 1245568.57 1589225023.00 2.00 2.00 Triangular msetwo 
output_btc_on_bch <- output

Effects on BSV

target <- "BSV"
base <- "BTC"
cutoff <- 630000
h <- 3600 * 24 * 28
h_short <- 3600 * 24 * 2
original <- TRUE
binselect <- "esmv"
p <- 4
halving_line_s <- as.POSIXct(
  c("2020-05-11 19:23:43"),
  origin = "1970-01-01",
  tz = "UTC"
  ) %>% 
  as.numeric()
halving_line_l <- as.POSIXct(
  c("2020-05-11 19:23:43"),
  origin = "1970-01-01",
  tz = "UTC"
  ) %>% 
  as.numeric()
linetype_l <- "blank"
linetype_s <- "solid"
target_before <- "BSV"
target_after <- "BCH" 

output <- 
  perform_rdd_reward_change(
    epoch_currency,
    target,
    base,
    cutoff,
    h,
    h_short,
    original,
    binselect,
    p,
    halving_line_l,
    halving_line_s,
    linetype_l,
    linetype_s,
    palette = colour_palette$bsv,
    target_before,
    target_after,
    target_line = FALSE
  )
Block time (s): Optimal h
term estimate std.error statistic p.value conf.low conf.high nobs.left nobs.right nobs.effective.left nobs.effective.right h.left h.right b.left b.right cutoff order.regression order.bias kernel bwselect
Conventional -161.25 58.34 -2.76 0.01 -275.60 -46.90 3977.00 4046.00 1561.00 713.00 936246.37 405649.05 1462716.39 730546.01 1589225023.00 2.00 2.00 Triangular msetwo
Bias-Corrected -180.90 58.34 -3.10 0.00 -295.25 -66.55 3977.00 4046.00 1561.00 713.00 936246.37 405649.05 1462716.39 730546.01 1589225023.00 2.00 2.00 Triangular msetwo
Robust -180.90 65.93 -2.74 0.01 -310.11 -51.68 3977.00 4046.00 1561.00 713.00 936246.37 405649.05 1462716.39 730546.01 1589225023.00 2.00 2.00 Triangular msetwo
Log of hash rate (h/s): Optimal h
term estimate std.error statistic p.value conf.low conf.high nobs.left nobs.right nobs.effective.left nobs.effective.right h.left h.right b.left b.right cutoff order.regression order.bias kernel bwselect
Conventional 0.86 0.11 7.63 0.00 0.64 1.08 3977.00 4046.00 1274.00 1060.00 770730.85 626490.09 1257671.68 1041695.68 1589225023.00 2.00 2.00 Triangular msetwo
Bias-Corrected 0.91 0.11 8.10 0.00 0.69 1.13 3977.00 4046.00 1274.00 1060.00 770730.85 626490.09 1257671.68 1041695.68 1589225023.00 2.00 2.00 Triangular msetwo
Robust 0.91 0.13 7.05 0.00 0.66 1.16 3977.00 4046.00 1274.00 1060.00 770730.85 626490.09 1257671.68 1041695.68 1589225023.00 2.00 2.00 Triangular msetwo 
output_btc_on_bsv <- output

Export

path <- "figuretable/summarize_arrival_rate_rdd"
figure_list <-
    list(
      btc_on_btc = output_btc_on_btc$figure,
      btc_on_bch = output_btc_on_bch$figure,
      btc_on_bsv = output_btc_on_bsv$figure
    )   
foreach (i = 1:length(figure_list)) %do% {
  name_i <- names(figure_list)[i]
  figure_i <- figure_list[[i]]
  foreach (j = 1:length(figure_i)) %do% {
    name_ij <- names(figure_i)[j]
    figure_ij <- figure_i[[j]]
    savename_ij <- 
      paste0(path, "/rdd_reward_change_for_", name_i, "_", name_ij, ".png")
    figure_ij %>%
      ggsave(
        filename = here::here(savename_ij),
        width = 4,
        height = 3
      )
  }
}
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result_list <-
    list(
      BTC = output_btc_on_btc$result,
      BCH = output_btc_on_bch$result,
      BSV = output_btc_on_bsv$result
    ) 
savename <- "figuretable/summarize_arrival_rate_rdd/effect_btc_halving.tex"
make_table_rdd(
    result_list,
    savename
  )
Log of hash rate (H/s)
BTC BCH BSV
Estimate -0.119 0.375 0.909
Std.error (0.132) (0.13) (0.129)
Nobs.left 4188 4011 3977
Nobs.right 3755 4020 4046
H.left 5.87e+05 7.18e+05 7.71e+05
H.right 9.28e+05 7.56e+05 6.26e+05
B.left 9.45e+05 1.26e+06 1.26e+06
B.right 1.45e+06 1.25e+06 1.04e+06
Order.regression 2 2 2
Kernel Triangular Triangular Triangular
Bwselect Msetwo Msetwo Msetwo

NULL

Reward change around BCH halving (esmv)

Effects on BTC

target <- "BTC"
base <- "BCH"
cutoff <- 630000
h <- 3600 * 24 * 28
h_short <- 3600 * 24 * 2
original <- TRUE
binselect <- "esmv"
p <- 4
halving_line_s <- as.POSIXct(
  c("2020-04-08 12:19:24",
    "2020-04-10 00:48:30"
    ),
  origin = "1970-01-01",
  tz = "UTC"
  ) %>% 
  as.numeric()
halving_line_l <- as.POSIXct(
  c("2020-04-08 12:19:24",
    "2020-04-10 00:48:30"
    ),
  origin = "1970-01-01",
  tz = "UTC"
  ) %>% 
  as.numeric()
linetype_l <- c("blank",
                "dashed"
                )
linetype_s <- c("solid",
                "dashed"
                )

output <- 
  perform_rdd_reward_change(
    epoch_currency,
    target,
    base,
    cutoff,
    h,
    h_short,
    original,
    binselect,
    p,
    halving_line_l,
    halving_line_s,
    linetype_l,
    linetype_s,
    palette = colour_palette$btc,
    target_before = "BSV",
    target_after = "BCH",
    target_line = TRUE
  )
Block time (s): Optimal h
term estimate std.error statistic p.value conf.low conf.high nobs.left nobs.right nobs.effective.left nobs.effective.right h.left h.right b.left b.right cutoff order.regression order.bias kernel bwselect
Conventional 39.15 54.03 0.72 0.47 -66.76 145.05 3769.00 4227.00 1017.00 1064.00 577363.80 574921.55 868795.73 1020698.99 1586348364.00 2.00 2.00 Triangular msetwo
Bias-Corrected 55.01 54.03 1.02 0.31 -50.90 160.91 3769.00 4227.00 1017.00 1064.00 577363.80 574921.55 868795.73 1020698.99 1586348364.00 2.00 2.00 Triangular msetwo
Robust 55.01 63.57 0.87 0.39 -69.59 179.60 3769.00 4227.00 1017.00 1064.00 577363.80 574921.55 868795.73 1020698.99 1586348364.00 2.00 2.00 Triangular msetwo
Log of hash rate (h/s): Optimal h
term estimate std.error statistic p.value conf.low conf.high nobs.left nobs.right nobs.effective.left nobs.effective.right h.left h.right b.left b.right cutoff order.regression order.bias kernel bwselect
Conventional -0.07 0.13 -0.53 0.60 -0.32 0.18 3769.00 4227.00 1209.00 798.00 682020.37 439978.73 1029314.51 757486.64 1586348364.00 2.00 2.00 Triangular msetwo
Bias-Corrected -0.10 0.13 -0.74 0.46 -0.35 0.16 3769.00 4227.00 1209.00 798.00 682020.37 439978.73 1029314.51 757486.64 1586348364.00 2.00 2.00 Triangular msetwo
Robust -0.10 0.15 -0.63 0.53 -0.39 0.20 3769.00 4227.00 1209.00 798.00 682020.37 439978.73 1029314.51 757486.64 1586348364.00 2.00 2.00 Triangular msetwo 
output_bch_on_btc <- output

Effects on BCH

target <- "BCH"
base <- "BCH"
cutoff <- 630000
h <- 3600 * 24 * 28
h_short <- 3600 * 24 * 2
original <- TRUE
binselect <- "esmv"
p <- 4
halving_line_s <- as.POSIXct(
  c("2020-04-08 12:19:24",
    "2020-04-10 00:48:30"
    ),
  origin = "1970-01-01",
  tz = "UTC"
  ) %>% 
  as.numeric()
halving_line_l <- as.POSIXct(
  c("2020-04-08 12:19:24",
    "2020-04-10 00:48:30"
    ),
  origin = "1970-01-01",
  tz = "UTC"
  ) %>% 
  as.numeric()
linetype_l <- c("blank",
                "dashed"
                )
linetype_s <- c("solid",
                "dashed"
                )

output <- 
  perform_rdd_reward_change(
    epoch_currency,
    target,
    base,
    cutoff,
    h,
    h_short,
    original,
    binselect,
    p,
    halving_line_l,
    halving_line_s,
    linetype_l,
    linetype_s,
    palette = colour_palette$bch,
    target_before,
    target_after,
    target_before = "BSV",
    target_after = "BCH",
    target_line = TRUE
  )
Block time (s): Optimal h
term estimate std.error statistic p.value conf.low conf.high nobs.left nobs.right nobs.effective.left nobs.effective.right h.left h.right b.left b.right cutoff order.regression order.bias kernel bwselect
Conventional 491.06 140.44 3.50 0.00 215.80 766.32 4030.00 3926.00 1453.00 543.00 866837.43 396390.80 1360964.63 829446.77 1586348364.00 2.00 2.00 Triangular msetwo
Bias-Corrected 543.20 140.44 3.87 0.00 267.94 818.46 4030.00 3926.00 1453.00 543.00 866837.43 396390.80 1360964.63 829446.77 1586348364.00 2.00 2.00 Triangular msetwo
Robust 543.20 156.70 3.47 0.00 236.07 850.32 4030.00 3926.00 1453.00 543.00 866837.43 396390.80 1360964.63 829446.77 1586348364.00 2.00 2.00 Triangular msetwo
Log of hash rate (h/s): Optimal h
term estimate std.error statistic p.value conf.low conf.high nobs.left nobs.right nobs.effective.left nobs.effective.right h.left h.right b.left b.right cutoff order.regression order.bias kernel bwselect
Conventional -0.66 0.14 -4.79 0.00 -0.94 -0.39 4030.00 3926.00 1593.00 652.00 947476.48 423065.41 1449261.81 916772.20 1586348364.00 2.00 2.00 Triangular msetwo
Bias-Corrected -0.71 0.14 -5.14 0.00 -0.98 -0.44 4030.00 3926.00 1593.00 652.00 947476.48 423065.41 1449261.81 916772.20 1586348364.00 2.00 2.00 Triangular msetwo
Robust -0.71 0.15 -4.60 0.00 -1.02 -0.41 4030.00 3926.00 1593.00 652.00 947476.48 423065.41 1449261.81 916772.20 1586348364.00 2.00 2.00 Triangular msetwo 
output_bch_on_bch <- output

Effects on BSV

target <- "BSV"
base <- "BCH"
cutoff <- 630000
h <- 3600 * 24 * 28
h_short <- 3600 * 24 * 2
original <- TRUE
binselect <- "esmv"
p <- 4
halving_line_s <- as.POSIXct(
  c("2020-04-08 12:19:24",
    "2020-04-10 00:48:30"
    ),
  origin = "1970-01-01",
  tz = "UTC"
  ) %>% 
  as.numeric()
halving_line_l <- as.POSIXct(
  c("2020-04-08 12:19:24",
    "2020-04-10 00:48:30"
    ),
  origin = "1970-01-01",
  tz = "UTC"
  ) %>% 
  as.numeric()
linetype_l <- c("blank",
                "dashed"
                )
linetype_s <- c("solid",
                "dashed"
                )

output <- 
  perform_rdd_reward_change(
    epoch_currency,
    target,
    base,
    cutoff,
    h,
    h_short,
    original,
    binselect,
    p,
    halving_line_l,
    halving_line_s,
    linetype_l,
    linetype_s,
    palette = colour_palette$bsv,
    target_before,
    target_after,
    target_before = "BSV",
    target_after = "BCH",
    target_line = TRUE
  )
Block time (s): Optimal h
term estimate std.error statistic p.value conf.low conf.high nobs.left nobs.right nobs.effective.left nobs.effective.right h.left h.right b.left b.right cutoff order.regression order.bias kernel bwselect
Conventional 133.57 63.69 2.10 0.04 8.74 258.40 4025.00 3909.00 1599.00 1408.00 944783.74 896331.97 1419150.23 1254411.61 1586348364.00 2.00 2.00 Triangular msetwo
Bias-Corrected 143.37 63.69 2.25 0.02 18.54 268.20 4025.00 3909.00 1599.00 1408.00 944783.74 896331.97 1419150.23 1254411.61 1586348364.00 2.00 2.00 Triangular msetwo
Robust 143.37 76.40 1.88 0.06 -6.37 293.11 4025.00 3909.00 1599.00 1408.00 944783.74 896331.97 1419150.23 1254411.61 1586348364.00 2.00 2.00 Triangular msetwo
Log of hash rate (h/s): Optimal h
term estimate std.error statistic p.value conf.low conf.high nobs.left nobs.right nobs.effective.left nobs.effective.right h.left h.right b.left b.right cutoff order.regression order.bias kernel bwselect
Conventional 0.37 0.17 2.20 0.03 0.04 0.71 4025.00 3909.00 759.00 430.00 448399.56 302888.69 785678.53 669985.78 1586348364.00 2.00 2.00 Triangular msetwo
Bias-Corrected 0.41 0.17 2.44 0.01 0.08 0.75 4025.00 3909.00 759.00 430.00 448399.56 302888.69 785678.53 669985.78 1586348364.00 2.00 2.00 Triangular msetwo
Robust 0.41 0.19 2.22 0.03 0.05 0.78 4025.00 3909.00 759.00 430.00 448399.56 302888.69 785678.53 669985.78 1586348364.00 2.00 2.00 Triangular msetwo 
output_bch_on_bsv <- output

Export

path <- "figuretable/summarize_arrival_rate_rdd"
figure_list <-
    list(
      bch_on_btc = output_bch_on_btc$figure,
      bch_on_bch = output_bch_on_bch$figure,
      bch_on_bsv = output_bch_on_bsv$figure
    )   
foreach (i = 1:length(figure_list)) %do% {
  name_i <- names(figure_list)[i]
  figure_i <- figure_list[[i]]
  foreach (j = 1:length(figure_i)) %do% {
    name_ij <- names(figure_i)[j]
    figure_ij <- figure_i[[j]]
    savename_ij <- 
      paste0(path, "/rdd_reward_change_for_", name_i, "_", name_ij, ".png")
    figure_ij %>%
      ggsave(
        filename = here::here(savename_ij),
        width = 4,
        height = 3
      )
  }
}
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result_list <-
    list(
      BTC = output_bch_on_btc$result,
      BCH = output_bch_on_bch$result,
      BSV = output_bch_on_bsv$result
    ) 
savename <- "figuretable/summarize_arrival_rate_rdd/effect_bch_halving.tex"
make_table_rdd(
    result_list,
    savename
  )
Log of hash rate (H/s)
BTC BCH BSV
Estimate -0.0951 -0.712 0.415
Std.error (0.151) (0.155) (0.187)
Nobs.left 3769 4030 4025
Nobs.right 4227 3926 3909
H.left 6.82e+05 9.47e+05 4.48e+05
H.right 4.4e+05 4.23e+05 3.03e+05
B.left 1.03e+06 1.45e+06 7.86e+05
B.right 7.57e+05 9.17e+05 6.7e+05
Order.regression 2 2 2
Kernel Triangular Triangular Triangular
Bwselect Msetwo Msetwo Msetwo

NULL

Reward change around BSV halving (esmv)

Effects on BTC

target <- "BTC"
base <- "BSV"
cutoff <- 630000
h <- 3600 * 24 * 28
h_short <- 3600 * 24 * 2
original <- TRUE
binselect <- "esmv"
p <- 4
halving_line_s <- as.POSIXct(
  c("2020-04-08 12:19:24",
    "2020-04-10 00:48:30"
    ),
  origin = "1970-01-01",
  tz = "UTC"
  ) %>% 
  as.numeric()
halving_line_l <- as.POSIXct(
  c("2020-04-08 12:19:24",
    "2020-04-10 00:48:30"
    ),
  origin = "1970-01-01",
  tz = "UTC"
  ) %>% 
  as.numeric()
linetype_l <- c("dashed",
                "blank"
                )
linetype_s <- c("dashed",
                "solid"
                )

output <- 
  perform_rdd_reward_change(
    epoch_currency,
    target,
    base,
    cutoff,
    h,
    h_short,
    original,
    binselect,
    p,
    halving_line_l,
    halving_line_s,
    linetype_l,
    linetype_s,
    palette = colour_palette$btc,
    target_before,
    target_after,
    target_before = "BSV",
    target_after = "BCH",
    target_line = TRUE
  )
Block time (s): Optimal h
term estimate std.error statistic p.value conf.low conf.high nobs.left nobs.right nobs.effective.left nobs.effective.right h.left h.right b.left b.right cutoff order.regression order.bias kernel bwselect
Conventional -42.40 48.74 -0.87 0.38 -137.93 53.13 3789.00 4219.00 1069.00 1387.00 610108.53 759188.77 908237.44 1147265.08 1586479710.00 2.00 2.00 Triangular msetwo
Bias-Corrected -40.86 48.74 -0.84 0.40 -136.39 54.67 3789.00 4219.00 1069.00 1387.00 610108.53 759188.77 908237.44 1147265.08 1586479710.00 2.00 2.00 Triangular msetwo
Robust -40.86 58.19 -0.70 0.48 -154.92 73.19 3789.00 4219.00 1069.00 1387.00 610108.53 759188.77 908237.44 1147265.08 1586479710.00 2.00 2.00 Triangular msetwo
Log of hash rate (h/s): Optimal h
term estimate std.error statistic p.value conf.low conf.high nobs.left nobs.right nobs.effective.left nobs.effective.right h.left h.right b.left b.right cutoff order.regression order.bias kernel bwselect
Conventional 0.10 0.11 0.96 0.34 -0.11 0.31 3789.00 4219.00 1354.00 1156.00 774201.66 616892.48 1163918.48 963795.30 1586479710.00 2.00 2.00 Triangular msetwo
Bias-Corrected 0.09 0.11 0.85 0.39 -0.12 0.30 3789.00 4219.00 1354.00 1156.00 774201.66 616892.48 1163918.48 963795.30 1586479710.00 2.00 2.00 Triangular msetwo
Robust 0.09 0.13 0.72 0.47 -0.16 0.34 3789.00 4219.00 1354.00 1156.00 774201.66 616892.48 1163918.48 963795.30 1586479710.00 2.00 2.00 Triangular msetwo 
output_bsv_on_btc <- output

Effects on BCH

target <- "BCH"
base <- "BSV"
cutoff <- 630000
h <- 3600 * 24 * 28
h_short <- 3600 * 24 * 2
original <- TRUE
binselect <- "esmv"
p <- 4
halving_line_s <- as.POSIXct(
  c("2020-04-08 12:19:24",
    "2020-04-10 00:48:30"
    ),
  origin = "1970-01-01",
  tz = "UTC"
  ) %>% 
  as.numeric()
halving_line_l <- as.POSIXct(
  c("2020-04-08 12:19:24",
    "2020-04-10 00:48:30"
    ),
  origin = "1970-01-01",
  tz = "UTC"
  ) %>% 
  as.numeric()
linetype_l <- c("dashed",
                "blank"
                )
linetype_s <- c("dashed",
                "solid"
                )

output <- 
  perform_rdd_reward_change(
    epoch_currency,
    target,
    base,
    cutoff,
    h,
    h_short,
    original,
    binselect,
    p,
    halving_line_l,
    halving_line_s,
    linetype_l,
    linetype_s,
    palette = colour_palette$bch,
    target_before,
    target_after,
    target_before = "BSV",
    target_after = "BCH",
    target_line = TRUE
  )

## Warning: Removed 1 rows containing missing values (geom_segment).

## Warning: Removed 1 rows containing missing values (geom_segment).
Block time (s): Optimal h
term estimate std.error statistic p.value conf.low conf.high nobs.left nobs.right nobs.effective.left nobs.effective.right h.left h.right b.left b.right cutoff order.regression order.bias kernel bwselect
Conventional -1264.95 190.75 -6.63 0.00 -1638.81 -891.10 3905.00 4014.00 253.00 746.00 221080.98 425386.43 552117.04 751204.10 1586479710.00 2.00 2.00 Triangular msetwo
Bias-Corrected -1339.16 190.75 -7.02 0.00 -1713.01 -965.30 3905.00 4014.00 253.00 746.00 221080.98 425386.43 552117.04 751204.10 1586479710.00 2.00 2.00 Triangular msetwo
Robust -1339.16 200.16 -6.69 0.00 -1731.47 -946.84 3905.00 4014.00 253.00 746.00 221080.98 425386.43 552117.04 751204.10 1586479710.00 2.00 2.00 Triangular msetwo
Log of hash rate (h/s): Optimal h
term estimate std.error statistic p.value conf.low conf.high nobs.left nobs.right nobs.effective.left nobs.effective.right h.left h.right b.left b.right cutoff order.regression order.bias kernel bwselect
Conventional 1.80 0.23 7.87 0.00 1.35 2.25 3905.00 4014.00 203.00 770.00 190546.63 454251.81 537558.55 711794.65 1586479710.00 2.00 2.00 Triangular msetwo
Bias-Corrected 1.89 0.23 8.25 0.00 1.44 2.34 3905.00 4014.00 203.00 770.00 190546.63 454251.81 537558.55 711794.65 1586479710.00 2.00 2.00 Triangular msetwo
Robust 1.89 0.24 7.85 0.00 1.42 2.36 3905.00 4014.00 203.00 770.00 190546.63 454251.81 537558.55 711794.65 1586479710.00 2.00 2.00 Triangular msetwo 
output_bsv_on_bch <- output

Effects on BSV

target <- "BSV"
base <- "BSV"
cutoff <- 630000
h <- 3600 * 24 * 28
h_short <- 3600 * 24 * 2
original <- TRUE
binselect <- "esmv"
p <- 4
halving_line_s <- as.POSIXct(
  c("2020-04-08 12:19:24",
    "2020-04-10 00:48:30"
    ),
  origin = "1970-01-01",
  tz = "UTC"
  ) %>% 
  as.numeric()
halving_line_l <- as.POSIXct(
  c("2020-04-08 12:19:24",
    "2020-04-10 00:48:30"
    ),
  origin = "1970-01-01",
  tz = "UTC"
  ) %>% 
  as.numeric()
linetype_l <- c("dashed",
                "blank"
                )
linetype_s <- c("dashed",
                "solid"
                )

output <- 
  perform_rdd_reward_change(
    epoch_currency,
    target,
    base,
    cutoff,
    h,
    h_short,
    original,
    binselect,
    p,
    halving_line_l,
    halving_line_s,
    linetype_l,
    linetype_s,
    palette = colour_palette$bsv,
    target_before,
    target_after,
    target_before = "BSV",
    target_after = "BCH",
    target_line = TRUE
  )
Block time (s): Optimal h
term estimate std.error statistic p.value conf.low conf.high nobs.left nobs.right nobs.effective.left nobs.effective.right h.left h.right b.left b.right cutoff order.regression order.bias kernel bwselect
Conventional 1009.75 219.18 4.61 0.00 580.15 1439.34 4037.00 3945.00 1656.00 364.00 982395.50 268597.15 1459256.74 685748.52 1586479710.00 2.00 2.00 Triangular msetwo
Bias-Corrected 1073.93 219.18 4.90 0.00 644.34 1503.52 4037.00 3945.00 1656.00 364.00 982395.50 268597.15 1459256.74 685748.52 1586479710.00 2.00 2.00 Triangular msetwo
Robust 1073.93 234.55 4.58 0.00 614.21 1533.64 4037.00 3945.00 1656.00 364.00 982395.50 268597.15 1459256.74 685748.52 1586479710.00 2.00 2.00 Triangular msetwo
Log of hash rate (h/s): Optimal h
term estimate std.error statistic p.value conf.low conf.high nobs.left nobs.right nobs.effective.left nobs.effective.right h.left h.right b.left b.right cutoff order.regression order.bias kernel bwselect
Conventional -1.40 0.21 -6.81 0.00 -1.80 -1.00 4037.00 3945.00 824.00 396.00 484624.96 295368.25 822366.86 638132.09 1586479710.00 2.00 2.00 Triangular msetwo
Bias-Corrected -1.50 0.21 -7.30 0.00 -1.90 -1.10 4037.00 3945.00 824.00 396.00 484624.96 295368.25 822366.86 638132.09 1586479710.00 2.00 2.00 Triangular msetwo
Robust -1.50 0.23 -6.55 0.00 -1.95 -1.05 4037.00 3945.00 824.00 396.00 484624.96 295368.25 822366.86 638132.09 1586479710.00 2.00 2.00 Triangular msetwo 
output_bsv_on_bsv <- output

Export

path <- "figuretable/summarize_arrival_rate_rdd"
figure_list <-
    list(
      bsv_on_btc = output_bsv_on_btc$figure,
      bsv_on_bch = output_bsv_on_bch$figure,
      bsv_on_bsv = output_bsv_on_bsv$figure
    )   
foreach (i = 1:length(figure_list)) %do% {
  name_i <- names(figure_list)[i]
  figure_i <- figure_list[[i]]
  foreach (j = 1:length(figure_i)) %do% {
    name_ij <- names(figure_i)[j]
    figure_ij <- figure_i[[j]]
    savename_ij <- 
      paste0(path, "/rdd_reward_change_for_", name_i, "_", name_ij, ".png")
    figure_ij %>%
      ggsave(
        filename = here::here(savename_ij),
        width = 4,
        height = 3
      )
  }
}
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result_list <-
    list(
      BTC = output_bsv_on_btc$result,
      BCH = output_bsv_on_bch$result,
      BSV = output_bsv_on_bsv$result
    ) 
savename <- "figuretable/summarize_arrival_rate_rdd/effect_bsv_halving.tex"
make_table_rdd(
    result_list,
    savename
  )
Log of hash rate (H/s)
BTC BCH BSV
Estimate 0.0905 1.89 -1.5
Std.error (0.126) (0.24) (0.229)
Nobs.left 3789 3905 4037
Nobs.right 4219 4014 3945
H.left 7.74e+05 1.91e+05 4.85e+05
H.right 6.17e+05 4.54e+05 2.95e+05
B.left 1.16e+06 5.38e+05 8.22e+05
B.right 9.64e+05 7.12e+05 6.38e+05
Order.regression 2 2 2
Kernel Triangular Triangular Triangular
Bwselect Msetwo Msetwo Msetwo

NULL